In urban areas, AI-driven sensor networks measure pollutants such as particulate matter, nitrogen dioxide and volatile organic compounds. Algorithms create real-time air quality maps, allowing the authorities to issue timely warnings and adjust traffic management and industrial operations.
In aquatic environments too, AI can effectively monitor water quality parameters such as pH, dissolved oxygen and contaminants. It can also provide early detection of chemical spills or algal blooms, making it possible to take rapid response measures to minimise the damage.
7. Waste management and recycling
Systems based on artificial intelligence can optimise waste collection routes by analysing historical data and real-time inputs, such as traffic conditions and current bin fill levels. This brings considerable cost savings, lower fuel consumption and a reduction in greenhouse gas emissions from collection vehicles.
Artificial intelligence can then help to reduce landfill waste by identifying opportunities for recycling and composting, improving the separation of recyclable from non-recyclable materials and ultimately reducing the volume of waste sent to landfill.
Advanced robotics and AI-based vision systems can sort materials more accurately than manual labour, increasing the quality and value of recycled materials.
8. Protecting the marine ecosystem
The dramatic decline that marine ecosystems have been facing in recent decades is well known, owing to many causes, from marine heatwaves and loss of biodiversity to sea level rise and acidification.
Artificial intelligence is already an ally in this battle for preservation. Autonomous underwater vehicles (AUVs) equipped with advanced artificial intelligence technologies are being used to explore and document the health of our oceans, supporting crucial conservation efforts.
These AUVs are able, for example, to detect subtle changes in coral reefs. By identifying signs of bleaching, disease or damage, artificial intelligence helps conservationists take prompt action to protect these critical habitats.
9. Disaster preparedness and response
According to the World Meteorological Organization (WMO), early detection and warning systems for natural disasters and extreme weather events can help save lives – and artificial intelligence is fundamental to achieving this.
By harnessing advanced algorithms, artificial intelligence can analyse historical data, current conditions and real-time data streams to provide timely warnings and facilitate rapid, informed responses. Faced with a large wildfire, for example, AI-based systems can monitor environmental conditions, including temperature, humidity, wind speed and historical fire behaviour. In this way they can also issue predictive fire risk assessments, helping the authorities allocate firefighting resources more effectively and making it possible to evacuate communities at risk before the fire reaches them.
10. Carbon capture and storage (CCS)
Carbon capture and storage (CCS) processes aim to capture CO2 emissions and store them underground to prevent their release into the atmosphere.
Although their effectiveness is still debated, it is a fact that artificial intelligence could optimise CCS processes by helping to select capture materials and fine-tune process conditions.
In addition, artificial intelligence can contribute to the continuous monitoring of underground storage sites to ensure the long-term integrity of the stored CO2, by analysing sensor data and predicting potential problems.
So far, then, this is the picture, predictive but partly already implemented or implementable, of the possibilities that AI offers in the fight for the ecological transition, against climate change and for a greener world.
Is it a rosy future, then, that awaits us? Or could the dangers inherent in the enormous power of AI also affect the environmental sector, leading to results opposite to the expectations and the optimistic proclamations?
I will try to explore this decisive aspect of our near future as well.
